A Linear Model to Estimate Faculty Member in The Iranian Medical Sciences Universities - bahram mohaghegh; niusha shahidi sadeghi; amir mohamadi; mohamad nazari; mohamad hosein salarianzadeh; amir ahamad akhavan; mohamad reza maleki; mostafa deilami; azam sadat hoseini; fatemeh talebi; ali akbar abedi; maasumeh faraj allahi (مجله علمی دانشگاه علوم پزشکی کردستان, 2024)
Background and Aim: Human resource planning of faculties in medical sciences universities is an important requirement to achieve the function of producing health workforce. This study aimed to develop a model for the estimation of faculties in universities of medical sciences. Materials and Methods: In this practical study, factors influencing the workload of faculty members were identified by quantitative and qualitative method. Data collection was done by document review, expert group interviews and curriculum analysis. Approaches based on curricula and the requirements of specialized boards were used to develop the model. Data entry and analysis were done in Microsoft Excel 2010. Results: To estimate the faculty members required for specialized, sub-specialized and fellowship courses of medicine, linear model consisting of the combined variable of the number of annual student admissions multiplied by the academic staff coefficient and the variable of the fixed number of faculty for each course, as well as the specialties required separately for each course, was constructed. The needed faculties for other courses were according to the other model consists of the independent variable of the number of students and a combined variable namely "faculty member coefficient", constructed of parameters including the number of credit hours obligated to be taught by a faculty member per semester, the optimum number of students in the class, the number of majors' semesters and the course's adjusted value. Conclusion: This model is an innovative method to estimate the needed faculties in Iranian universities of medical sciences that could raise the efficiency of health workforce's production. Key words: Faculty member, Model, Estimation, Medical Sciences University.